Engineering Commons^™

Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave

Browse all Theses and Dissertations

Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …

Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon

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Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who …

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

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Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

Carbon Nanotube-Coated Scaffolds For Tissue Engineering Applications, Soham Dipakbhai Parikh

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Carbon Nanotubes (CNTs) have beneficial properties for cell scaffolding, which has translated into effective growth of bone, muscle, and cardiac cells. However, loose carbon nanotubes can cause in vivo toxicity. To reduce this risk, our team has developed biomimetic scaffolds with multiscale hierarchy where carpet-like CNT arrays are covalently bonded to larger biocompatible substrates. In this study, we have tested such scaffolds in two distinct types of biomedical applications involving glioblastoma and keratinocyte cells. The growth of glioblastoma (GBM) cells on our CNT-coated biomimetic scaffolds was evaluated to check their suitability as a potential chemotherapy-loaded implant for GBM patient treatment. …

Developments Of Advanced Cathodes And Stabilized Zinc Anodes For High-Performance Aqueous Zinc-Ion Batteries, Xiujuan Chen

Graduate Theses, Dissertations, and Problem Reports (ETD)

Aqueous rechargeable zinc-ion batteries (ZIBs) have attracted considerable attention as one of the most promising energy storage systems for the grid-scale application owing to the natural merits of metallic Zn, including a high theoretical capacity, suitable redox potential, low cost, high safety, and eco-friendliness. However, the existing aqueous ZIBs are far from satisfying the requirements of practical applications. Significant challenges hindering the further development of ZIBs come from the low utilization and poor cycling stability of cathodes and limited reversibility of Zn anodes associated with dendrite growth, corrosion, and passivation. To date, enormous efforts have been devoted to developing high-performance …

Static And Dynamic Analysis Of Composite Plates Using The Monna Finite Element, Mohamed Emadeldin Omar Abdelhadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Composite materials are replacing metals in many fields due to their favorable qualities such as strength-to-weight ratio, fatigue characteristics, and corrosion resistance. An efficient, versatile, and accurate composite plate element applicable to the dynamic analysis of composite plates would help the advancement of composites tremendously.

The objective of this research is to analyze composite plates using the classical laminated plate theory (CLPT), first-order deformation theory (FSDT), and higher-order deformation theory (HSDT) with the applicable finite element modeling (FEM) for each theory. This thesis investigates which theory is more efficient and accurate and evaluates the benefits of using an h-p-version …

Multivariate Time Series Classification Of Sensor Data From An Industrial Drying Hopper: A Deep Learning Approach, Md Mushfiqur Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

In recent years, the advancement of industry 4.0 and smart manufacturing has made a large number of industrial process data attainable with the use of sensors installed in the machineries. This thesis proposes an experimental predictive maintenance framework for an industrial drying hopper so that it can detect any unusual event in the hopper which reduces the risk of erroneous fault diagnosis in the manufacturing shop floor. The experimental framework uses Deep Learning (DL) algorithms in order to classify Multivariate Time Series (MTS) data into two categories- failure or unusual events and regular events, thus formulating the problem as binary …

An End-To-End Face Recognition System Evaluation Framework, James Andrew Duncan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The performance of face recognition system components is traditionally reported using metrics such as the Receiver Operating Characteristic (ROC), Cumulative Match Characteristic (CMC), and Identification Error Tradeoff (IET). Recently, new metrics have been published to take advantage of annotation-dense datasets such as IARPA Janus Benchmark-Surveillance and IARPA Janus Benchmark-Multi Domain Face to describe end-to-end face recognition system performance. Unlike traditional (component-level) analysis, end-to-end analysis of a system produces a metric proportional to the experience of a user of a face recognition system. The End-to-End Cumulative Match Characteristic (E2ECMC) summarizes detection, identity consolidation, and identity retrieval performance. The End-to-End Subject Cumulative …

Evaluation Of Murrell’S Ekf-Based Attitude Estimation Algorithm For Exploiting Multiple Attitude Sensor Configurations, Sharanabasaweshwara Asundi, Norman Fitz-Coy, Haniph Latchman

Mechanical & Aerospace Engineering Faculty Publications

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell's implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell's EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its …

Mechanism For The Unfolding Of The Top7 Protein In Steered Molecular Dynamics Simulations As Revealed By Mutual Information Analysis, Ognjen Perišić, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

We employed mutual information (MI) analysis to detect motions affecting the mechanical resistance of the human-engineered protein Top7. The results are based on the MI analysis of pair contact correlations measured in steered molecular dynamics (SMD) trajectories and their statistical dependence on global unfolding. This study is the first application of the MI analysis to SMD forced unfolding, and we furnish specific SMD recommendations for the utility of parameters and options in the TimeScapes package. The MI analysis provided a global overview of the effect of perturbation on the stability of the protein. We also employed a more conventional trajectory …

Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty

VMASC Publications

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …

Modeling The Effects Of Religious Belief And Affiliation On Prosociality, Luke Galen, Ross Gore, F. Leron Shults

VMASC Publications

To what extent do supernatural beliefs, group affiliation, and social interaction produce values and behaviors that benefit others, i.e., prosociality? Addressing this question involves multiple variables interacting within complex social networks that shape and constrain the beliefs and behaviors of individuals. We examine the relationships among some of these factors utilizing data from the World Values Survey to inform the construction of an Agent-Based Model. The latter was able to identify the conditions under which - and the mechanisms by which - the prosociality of simulated agents was increased or decreased within an "artificial society" designed to reflect real world …

Internet-Of-Things Devices In Support Of The Development Of Echoic Skills Among Children With Autism Spectrum Disorder, Krzysztof J. Rechowicz, John B. Stull, Michelle M. Hascall, Saikou Y. Diallo, Kevin J. O'Brien

VMASC Publications

A significant therapeutic challenge for people with disabilities is the development of verbal and echoic skills. Digital voice assistants (DVAs), such as Amazon’s Alexa, provide networked intelligence to billions of Internet-of-Things devices and have the potential to offer opportunities to people, such as those diagnosed with autism spectrum disorder (ASD), to advance these necessary skills. Voice interfaces can enable children with ASD to practice such skills at home; however, it remains unclear whether DVAs can be as proficient as therapists in recognizing utterances by a developing speaker. We developed an Alexa-based skill called ASPECT to measure how well the DVA …

Vind: A Blockchain-Enabled Supply Chain Provenance Framework For Energy Delivery Systems, Eranga Bandara, Sachin Shetty, Deepak Tosh, Xueping Liang

VMASC Publications

Enterprise-level energy delivery systems (EDSs) depend on different software or hardware vendors to achieve operational efficiency. Critical components of these systems are typically manufactured and integrated by overseas suppliers, which expands the attack surface to adversaries with additional opportunities to infiltrate into EDSs. Due to this reason, the risk management of the EDS supply chain is crucial to ensure that we are knowledgeable about the vulnerabilities in software and hardware components that comprise any critical part, quantifiable risk metrics to assess the severity and exploitability of the attack, and provide remediation solutions that can influence a prioritized mitigation plan. There …

Methods For Weighting Decisions To Assist Modelers And Decision Analysts: A Review Of Ratio Assignment And Approximate Techniques, Barry Ezell, Christopher J. Lynch, Patrick T. Hester

VMASC Publications

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques …

Fuzzy Cognitive Map-Based Knowledge Representation Of Hazardous Industrial Operations, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Caterina Fusto, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

Hazardous industrial operations are highly stochastic, still human-dependent, and risky. Operators working in such an environment must understand the complex interrelation between several factors contributing to safe and effective operations. Therefore, being able to predict the effects of their actions on provoking or mitigating possible accidents is crucial. This study aims to utilize fuzzy cognitive maps (FCM) to model the expert’s reasoning about occupational health and safety (OHS) in confined space. This knowledge is used by operators to build their mental models. The developed FCM displays all the possible incidents of a confined space and links these incidents with all …

Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz

VMASC Publications

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …

Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano

VMASC Publications

The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …

Digital Twins For Manufacturing And Logistics Systems: Is Simulation Practice Ready?, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

This article provides a theoretical contribution to the state-of-the-art of digital twins for manufacturing and logistics systems. The primary goal of this paper is to draw attention to the gap between the theoretical framework of digital twins in manufacturing and supply chain and their practical implementation from a simulation modeling point of view. Therefore, highlighting the recent innovations in the simulation practice that could provide the basis for digital twins with high levels of data integration, automation, and smart capabilities. This study follows a comparative approach to analyzing theoretical and technical readiness for developing digital twins with high fidelity and …

Computational Decision Support For The Covid-19 Healthcare Coalition, Andreas Tolk, Christopher Glazner, Joseph Ungerleider

VMASC Publications

In the early months of 2020, the SARS-CoV-2 Coronavirus took the world by surprise, resulting in the COVID-19 pandemic that has caused significant loss of lives and challenged the sustainability of our health care systems. In mid-March, it became obvious that government and communities had to react immediately. Under the lead of the Mayo Clinic and The MITRE Corporation, the COVID-19 Healthcare Coalition (C19HCC) was established as a coordinated public-interest, private-sector response. The coalition brought healthcare organizations, technology firms, nonprofits, academia, and startups to support supply chains, inform coordinated social policies, and provide data-driven insights to protect people and preserve …

Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee

Community & Environmental Health Faculty Publications

Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …

Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha

Civil & Environmental Engineering Faculty Publications

Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online …

Exploring And Visualizing Spatial Effects And Patterns In Ride-Sourcing Trip Demand And Characteristics, Bishoy Kelleny, Sherif Ishak

Civil & Environmental Engineering Faculty Publications

The complex demand pattern of ride-sourcing remains to be a challenge to transportation modeling practitioners due to the infancy and the inherently dynamic nature of the ride-sourcing system. Spatial effects exploration and analysis protocols can provide informative insights on the underlying structure of demand and trip characteristics. Those protocols can be thought of as an opportunistic strategy to alleviate the complexity and help specifying the appropriate econometric models for the system. Spatial effects exploration is comparable to point pattern analysis, in which, signals from spatial entities, like census tracts, can be analyzed statistically to reveal whether a specific phenomenon respective …

Laboratory Study Of The Effects Of Flexible Vegetation On Solute Diffusion In Unidirectional Flow, Sha Lou, Hao Wang, Hongzhe Liu, Guihui Zhong, Larisa Dorzhievna Radnaeva, Elena Nikitina, Gangfeng Ma, Shuguang Liu

Civil & Environmental Engineering Faculty Publications

Background

Flexible vegetation is an important part of the riverine ecosystem, which can reduce flow velocity, change turbulence structure, and affect the processes of solute transport. Compared with the flow with rigid vegetation, which has been reported in many previous studies, bending of flexible vegetation increases the complexity of the flow-vegetation-solute interactions. In this study, laboratory experiments are carried out to investigate the influence of flexible vegetation on solute transport, and methods for estimating the lateral and longitudinal diffusion coefficients in the rigid vegetated flow are examined for their applications to the flow with flexible vegetation.

Results

The experimental observations …

Online Bus Speed Prediction With Spatiotemporal Interaction: A Laplace Approximation-Based Bayesian Approach, Haipeng Cui, Kun Xie, Bin Hu, Hangfei Lin

Civil & Environmental Engineering Faculty Publications

This study proposes a novel Bayesian hierarchical approach for online bus speed prediction by explicitly accounting for the spatiotemporal interaction (STI) of speed observations. The use of Laplace approximation can expedite the estimation of Bayesian models and enable the implementation of online prediction. Large numbers of trials are carried out to identify significant predictors and the optimal length of the look-back time window to achieve the highest prediction accuracy. The spatiotemporal interacting patterns are also explored, and results show that the Type IV model assuming the structured spatial effect interacts with the structured temporal effect can best accommodate the bus …

Wave Climate Associated With Changing Water Level And Ice Cover In Lake Michigan, Chenfu Huang, Longhuan Zhu, Gangfeng Ma, Guy A. Meadows, Pengfei Xue

Civil & Environmental Engineering Faculty Publications

Detailed knowledge of wave climate change is essential for understanding coastal geomorphological processes, ecosystem resilience, the design of offshore and coastal engineering structures and aquaculture systems. In Lake Michigan, the in-situ wave observations suitable for long-term analysis are limited to two offshore MetOcean buoys. Since this distribution is inadequate to fully represent spatial patterns of wave climate across the lake, a series of high-resolution SWAN model simulations were performed for the analysis of long-term wave climate change for the entirety of Lake Michigan from 1979 to 2020. Model results were validated against observations from two offshore buoys and 16 coastal …

Large-Scale Variation In Wave Attenuation Of Oyster Reef Living Shorelines And The Influence Of Inundation Duration, Rebecca L. Morris, Megan K. La Peyre, Bret M. Webb, Danielle A. Marshall, Donna M. Bilkovic, Just Cebrian, Giovanna Mcclenachan, Kelly M. Kibler, Linda J. Walters, David Bushek, Eric L. Sparks, Nigel A. Temple, Joshua Moody, Kory Angstadt, Joshua Goff, Maura Boswell, Paul Sacks, Stephen E. Swearer

Civil & Environmental Engineering Faculty Publications

One of the paramount goals of oyster reef living shorelines is to achieve sustained and adaptive coastal protection, which requires meeting ecological (i.e., develop a self-sustaining oyster population) and engineering (i.e., provide coastal defense) targets. In a large-scale comparison along the Atlantic and Gulf coasts of the United States, the efficacy of various designs of oyster reef living shorelines at providing wave attenuation was evaluated accounting for the ecological limitations of oysters with regards to inundation duration. A critical threshold for intertidal oyster reef establishment is 50% inundation duration. Living shorelines that spent less than half of the time ( …

Strengthening Prestressed Concrete Bridge Girders And Building Beams With Carbon Fiber Reinforced Polymer Sheets, Herish A. Hussein, Zia Razzaq

Civil & Environmental Engineering Faculty Publications

The effect of Carbon Fiber Reinforced Polymer (CFRP) retrofitting and concrete type on the flexural strength of prestressed concrete I-section girders used in bridges and beams in buildings is investigated. Non-linear moment-curvature relationships are predicted using an iterative algorithm for both non-retrofitted and CFRP-retrofitted prestressed concrete girder and beam cross-sections with various concrete types. Two different CFRP-retrofitting schemes are analyzed for comparing their effectiveness. It is found that although non-retrofitted beam section exhibits greater ductility, the use of CFRP retrofitting in both tension and compression regions simultaneously results in a significant increase in flexural strength. It is also found that …

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …